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Malware Detection

Malware Detection is a significant part of endpoint security including workstations, servers, cloud instances, and mobile devices. Malware Detection is used to detect and identify malicious activities caused by malware. With the increase in the variety of malware activities on CMS based websites such as malicious malware redirects on WordPress site (Aka, WordPress Malware Redirect Hack) where the site redirects to spam, being the most widespread, the need for automatic detection and classifier amplifies as well. The signature-based Malware Detection system is commonly used for existing malware that has a signature but it is not suitable for unknown malware or zero-day malware

Source: The Threat of Adversarial Attacks on Machine Learning in Network Security - A Survey

Papers

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Showing 201–250 of 431 papers

TitleStatusHype
Out of Distribution Data Detection Using Dropout Bayesian Neural Networks—0
StratDef: Strategic Defense Against Adversarial Attacks in ML-based Malware Detection—0
IoT Malware Detection Architecture using a Novel Channel Boosted and Squeezed CNN—0
On The Empirical Effectiveness of Unrealistic Adversarial Hardening Against Realistic Adversarial AttacksCode0
Efficient and Robust Classification for Sparse Attacks—0
Android Malware Detection using Feature Ranking of Permissions—0
RoboMal: Malware Detection for Robot Network Systems—0
Graph Neural Network-based Android Malware Classification with Jumping Knowledge—0
Cross-Language Binary-Source Code Matching with Intermediate Representations—0
Adversarial Attacks against Windows PE Malware Detection: A Survey of the State-of-the-ArtCode1
Benchmark Static API Call Datasets for Malware Family Classification—0
ORSA: Outlier Robust Stacked Aggregation for Best- and Worst-Case Approximations of Ensemble Systems\—0
HAPSSA: Holistic Approach to PDF Malware Detection Using Signal and Statistical Analysis—0
OMD: Orthogonal Malware Detection Using Audio, Image, and Static Features—0
"How Does It Detect A Malicious App?" Explaining the Predictions of AI-based Android Malware Detector—0
On the Effectiveness of Interpretable Feedforward Neural Network—0
Task-Aware Meta Learning-based Siamese Neural Network for Classifying Obfuscated Malware—0
A Modern Analysis of Aging Machine Learning Based IoT Cybersecurity Methods—0
EvadeDroid: A Practical Evasion Attack on Machine Learning for Black-box Android Malware DetectionCode0
LSTM Hyper-Parameter Selection for Malware Detection: Interaction Effects and Hierarchical Selection Approach—0
Can We Leverage Predictive Uncertainty to Detect Dataset Shift and Adversarial Examples in Android Malware Detection?Code1
DRo: A data-scarce mechanism to revolutionize the performance of Deep Learning based Security Systems—0
DexRay: A Simple, yet Effective Deep Learning Approach to Android Malware Detection based on Image Representation of BytecodeCode1
ML-based IoT Malware Detection Under Adversarial Settings: A Systematic Evaluation—0
Mal2GCN: A Robust Malware Detection Approach Using Deep Graph Convolutional Networks With Non-Negative Weights—0
heterogeneous temporal graph transformer: an intelligent system for evolving android malware detectionCode1
Leveraging Uncertainty for Improved Static Malware Detection Under Extreme False Positive Constraints—0
PDF-Malware: An Overview on Threats, Detection and Evasion Attacks—0
Decision-forest voting scheme for classification of rare classes in network intrusion detection—0
Malware Analysis with Artificial Intelligence and a Particular Attention on Results Interpretability—0
Dynamic detection of mobile malware using smartphone data and machine learning—0
Android Security using NLP Techniques: A Review—0
Data Augmentation for Opcode Sequence Based Malware Detection—0
Artificial Neural Network for Cybersecurity: A Comprehensive Review—0
Evading Malware Classifiers via Monte Carlo Mutant Feature DiscoveryCode0
Towards an Automated Pipeline for Detecting and Classifying Malware through Machine Learning—0
Enhancing Robustness of Neural Networks through Fourier Stabilization—0
Multi-Task Hierarchical Learning Based Network Traffic AnalyticsCode1
MalPhase: Fine-Grained Malware Detection Using Network Flow Data—0
Learning Security Classifiers with Verified Global Robustness PropertiesCode1
Analyzing Machine Learning Approaches for Online Malware Detection in Cloud—0
Federated Learning for Malware Detection in IoT DevicesCode1
A Novel Malware Detection Mechanism based on Features Extracted from Converted Malware Binary Images—0
Early Detection of In-Memory Malicious Activity based on Run-time Environmental Features—0
Deep Learning for Android Malware Defenses: a Systematic Literature ReviewCode1
Word Embedding Techniques for Malware Evolution Detection—0
NF-GNN: Network Flow Graph Neural Networks for Malware Detection and Classification—0
Malware Classification Using Long Short-Term Memory Models—0
Malware Classification with GMM-HMM Models—0
Identification of Significant Permissions for Efficient Android Malware Detection—0
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